langgraph-streaming

What problem does it solve?

This Skill helps developers implement and understand various streaming capabilities within LangGraph, enabling real-time feedback and efficient data flow for LLM applications.

Core Features & Use Cases

• Multiple Stream Modes: Supports values, updates, messages, custom, debug, checkpoints, and tasks for diverse output needs.
• LLM Token Streaming: Enables token-by-token streaming for chat UIs.
• Custom Event Streaming: Allows emitting user-defined events via StreamWriter.
• Subgraph Streaming: Facilitates monitoring of nested agent execution.
• Async Support: Provides patterns for asynchronous streaming.
• Use Case: Building a customer support chatbot that streams LLM responses token-by-token, displays real-time processing status updates, and logs detailed debug information for troubleshooting.

Quick Start

Use the langgraph-streaming skill to stream LLM tokens in real-time for chat UI display.